I am a Data Scientist and GIS Manager with a decade of experience solving high-stakes problems in regulated industries.
Currently, I lead the geospatial program for the Tennessee Division of Forestry, where I architect the data infrastructure and
Python-driven automation that protects millions of acres of natural resources.
My career is built on a foundation of efficiency consulting. Whether I am building Multi-Criteria Decision Analysis (MCDA)
models for the next generation of nuclear energy or establishing version-controlled GitHub repositories for statewide agencies,
my goal is the same: to turn massive, complex datasets into clear, strategic recommendations.
My Philosophy: No "Black Boxes"
I take deep pride in my professional judgment by avoiding the "black box"—where solutions are buried in unnecessarily complicated models.
I believe that while our tools (like Google Gemini and Vertex AI) are incredibly powerful, the quality of our decisions relies on transparent insights.
As George Box famously said, "All models are wrong, but some are useful." My mission is to ensure every model I build is useful, reproducible,
and aligned with institutional goals.
Beyond the Terminal
Before I was a Data Scientist, I was an Airborne Infantry Team Lead in the U.S. Army, a background that instilled in me the "efficient execution"
and "positive energy" I bring to every technical team I lead.
The Tech Stack
I work at the edge of what’s possible in spatial science and data engineering. My daily toolkit includes:
- Languages: Python (Pandas/NumPy), SQL, JavaScript, and HTML/CSS.
- Modern Dev: GitHub CI/CD, Infrastructure as Code, and RESTful APIs.
- AI/LLM: Developing custom agents in GCP and Vertex AI to accelerate analysis and roadmapping.
When I’m not automating data pipelines or exploring the DeFi ecosystem, I’m likely finding my own flow in the great outdoors.
You can frequently find me kayaking the Gauley River, climbing at the Lily Boulders, or generally causing mischief in the
wilderness with my partner, Jess, and our two dogs, Willow and Coconut.
